AWS HPC Blog
Category: AWS Batch
Advancing research in the cloud: AWS announces expanded training resources
AWS is investing in researcher training with new learning plans for HPC, quantum, stats, AI/ML & generative AI. Check out the details!
Improve engineering productivity using AWS Engineering License Management
This post was contributed by Eran Brown, Principal Engagement Manager, Prototyping Team, Vedanth Srinivasan, Head of Solutions, Engineering & Design, Edmund Chute, Specialist SA, Solution Builder, Priyanka Mahankali, Senior specialist SA, Emerging Domains For engineering companies, the cost of Computer Aided Design and Engineering (CAD/CAE) tools can as high as 20% of product development cost. […]
Optimizing compute-intensive tasks on AWS
Optimizing workloads for performance and cost-effectiveness is crucial for businesses of all sizes – and especially helpful for workloads in the cloud, where there are a lot of levers you can pull to tune how things run. AWS offers a vast array of instance types in Amazon Elastic Compute Cloud (Amazon EC2) – each with […]
Building your digital twin solution using the Digital Twin Framework on AWS
This post was contributed by Jeremiah Habets, Ross Pivovar, Pramod Daya, Pallavi Chari, and Adam Rasheed from AWS Customers tell us that they’re increasingly seeking holistic digital twin solutions spanning IoT, spatial computing, and predictive modeling domains. Integrating these diverse technical stacks presents challenges for builders. In a prior post, we described a four-level Digital […]
Automotive component design at Nifco using generative AI and diffusion models
Combining generative AI with AWS services, Nifco USA is exploring new frontiers in structural design. See how they’re using diffusion models, SageMaker, and Batch to create game-changing lightweight auto parts.
Use Terraform to deploy a complete AWS Batch environment on Amazon EKS
Harness the power of AWS Batch on Amazon EKS with this new Terraform blueprint. It provides a complete template to create robust batch processing in the cloud. An easy button you shouldn’t miss.
Harnessing the power of agent-based modeling for equity market simulation and strategy testing
Financial professionals: Simulate realistic market conditions with Simudyne’s agent-based modeling on AWS and Red Hat OpenShift. Learn how HKEX leverages these insights.
Recent improvement to Open MPI AllReduce and the impact to application performance
Our team engineered some Open MPI optimizations for EFA to enhance performance of HPC codes running in the cloud. By improving MPI_AllReduce they improved scaling – matching commercial MPIs. Tests show gains for apps including Code Saturne and OpenFOAM on both Arm64 and x86 instances. Check out how these tweaks can speed up your HPC workloads in the cloud.
Near-real-time energy production forecasts with NVIDIA Earth-2 and AWS Batch
Using AWS Batch and NVIDIA Earth-2, we built a scalable workflow that explores millions of scenarios at a fraction of the cost of traditional methods. This innovative approach not only provides rapid energy calculations, but also shows the potential of AI-driven meteorology.
Harnessing the power of large language models for agent-based model development
Want to build agent-based models without deep expertise? Our latest blog post explores using Claude 3 Sonnet to tap into knowledge and accelerate ABM development.